Analytics Engineer
Role Overview
Own what happens to data after it lands in the BigQuery warehouse, including transformation, modelling, the semantic layer and reporting.
This is one of two engineering roles in the Business Intelligence team; the Data Engineer owns the platform and data ingestion, with some shared skills and overlap.
The company is rolling out safe self-serve AI analytics, which depends on models that reflect consistent business metric definitions.
Key Skills for This Role
Full Job Posting
Role overview
Own what happens to data after it lands in the BigQuery warehouse, including transformation, modelling, the semantic layer and reporting.
This is one of two engineering roles in the Business Intelligence team; the Data Engineer owns the platform and data ingestion, with some shared skills and overlap.
The company is rolling out safe self-serve AI analytics, which depends on models that reflect consistent business metric definitions.
What you will do
- Own the Dataform transformation layer end to end, including models, dependency graph, tests and documentation between raw BigQuery data and business outputs.
- Build a semantic layer with consistent definitions for revenue, margin, customer and order metrics across reports and AI tools.
- Own Looker Studio reporting, from executive dashboards to self-serve datasets for analysts and the wider business.
- Structure and document models for reliable self-serve AI analytics and decide where appropriate boundaries sit.
- Partner with marketing, trading, operations and finance to identify measurement needs and build models to address them.
- Drive data quality with tests and checks, and agree data contracts and conventions with the Data Engineer.
Ideal candidate
- Proven analytics engineering experience, including production models that other people depend on.
- Excellent SQL and hands-on Dataform or dbt experience, including testing and documentation; BigQuery experience is ideal.
- Strong data modelling skills and the ability to shape messy source systems into useful business models and explain design choices.
- Experience with a semantic layer or shared metric definitions, a BI tool such as Looker Studio or Looker, and a Git and CI/CD workflow.
- Able to turn vague business questions into working models, explain thinking clearly to non-technical teams, and maintain a high bar for detail.
- Python, ecommerce or DTC experience, and Google's marketing stack are bonuses.
Nice to have
- Python for tooling, testing or automation.
- Familiarity with Cloud Run, Cloud Scheduler or infrastructure-as-code.
- Experience implementing or evaluating self-serve AI analytics tooling.
- Comfort with vector databases, embeddings or semantic search.
- Working knowledge of Google Analytics, Google Tag Manager, Google Ads and Google Search Console.
- Experience in ecommerce, DTC or retail.
Success measures
Accurate, consistent numbers the business trusts.
Teams answering standard questions themselves without raising a ticket.
Decisions across marketing, trading, operations and finance made using consistent modelled data.
Benefits
- Exclusive staff discounts, private healthcare, a birthday day off and a pension scheme.
- Unique bonus scheme, cycle to work scheme, retail discounts, and staff socials and events.
- State-of-the-art campus, work from home on Fridays, and on-site refreshments.
About Protein Works
Founded in 2012, Protein Works describes itself as a £50m business with five consecutive years of double-digit growth and a new campus in Liverpool.
The company operates as a brand, retailer, manufacturer and fulfilment operation, with these activities under one roof.
Apply for this job in 1 click
Skip the repetitive application forms
Install the Base Career Chrome Extension and autofill job applications across major job boards with your profile.
Trusted by over 500,000 job seekers on Base Career